Artificial neural networks for real-time estimation of basic waveforms of voltages and currents

A. Cichocki, T. Lobos

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

New parallel algorithms for estimation of parameters of sinewave contaminated by noise are proposed. The problem of estimation is formulated as an optimization problem and solved by using the gradient descent method. Algorithms based on the least absolute value, the least-squares and the minimax (Chebyshev) criteria are developed and compared. The implementation of algorithms by an appropriate neural network is also given. Illustrative computer simulation results confirm validity and high performance of the proposed solution.

Original languageEnglish
Title of host publication1993 IEEE Power Industry Computer Applications Conference
PublisherPubl by IEEE
Pages357-363
Number of pages7
ISBN (Print)078031302X, 9780780313026
DOIs
Publication statusPublished - 1993
Externally publishedYes
Event1993 IEEE Power Industry Computer Applications Conference - Scottsdale, AZ, USA
Duration: 4 May 19937 May 1993

Publication series

Name1993 IEEE Power Industry Computer Applications Conference

Conference

Conference1993 IEEE Power Industry Computer Applications Conference
CityScottsdale, AZ, USA
Period4/05/937/05/93

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